Online caching policies based on gradient methods have also been studied in the stochastic request setting, leading to Robbins-Monro/stochastic approximation algorithms (see, e.g., [1]}, [2]}). Though related to OCO, guarantees are very different than the regret metric we study here.
Many works have also explored the offline, network-wide static allocation of contents, presuming demand is known [3]}, [4]}, [5]}.
We differ from the work above, as we consider adversarial requests.
